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Machine Learning and AI Applications in Healthcare

Ce cours n'est pas disponible en Français (France)

Nous sommes actuellement en train de le traduire dans plus de langues.

Machine Learning and AI Applications in Healthcare

Ce cours fait partie de Certificat Professionnel Microsoft Azure AI in Healthcare

Instructeur : Microsoft

Inclus avec

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

4 semaines à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

4 modules

Obtenez un aperçu d'un sujet et apprenez les principes fondamentaux.

niveau Intermédiaire

Expérience recommandée

4 semaines à compléter

à 10 heures par semaine

Planning flexible

Apprenez à votre propre rythme

Ce que vous apprendrez

Build and deploy machine learning models using healthcare datasets and Azure AI tools.
Create predictive analytics solutions for patient outcomes and clinical decision support.
Evaluate and interpret AI models to ensure fairness, reliability, and actionable insights in healthcare.

Compétences que vous acquerrez

Catégorie : Responsible AI
Catégorie : Dashboard Creation
Catégorie : Predictive Modeling
Catégorie : Medical Imaging
Catégorie : Machine Learning Methods
Catégorie : Data Visualization Software
Catégorie : Artificial Intelligence and Machine Learning (AI/ML)
Catégorie : MLOps (Machine Learning Operations)
Catégorie : Data Presentation
Catégorie : Health Equity
Catégorie : Model Evaluation
Catégorie : Azure Synapse Analytics
Catégorie : Predictive Analytics
Catégorie : Machine Learning
Catégorie : Image Analysis
Catégorie : Model Training

Outils que vous découvrirez

Catégorie : Microsoft Azure
Catégorie : Model Deployment
Catégorie : AI Workflows
Catégorie : Power BI

Détails à connaître

Certificat partageable

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Ce cours fait partie de la Certificat Professionnel Microsoft Azure AI in Healthcare

Lorsque vous vous inscrivez à ce cours, vous êtes également inscrit(e) à ce Certificat Professionnel.

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Il y a 4 modules dans ce cours

This comprehensive course bridges machine learning fundamentals with specialized healthcare AI applications, guiding students through the complete AI model lifecycle from data preprocessing to production deployment. You'll master core ML algorithms and deep learning architectures while gaining hands-on experience building medical imaging analysis systems, predictive models for patient outcomes, and clinical NLP applications using Azure AI services including Azure Machine Learning, Cognitive Services, and Computer Vision. The curriculum emphasizes healthcare-specific challenges including rigorous clinical validation methodologies that satisfy regulatory requirements, comprehensive bias detection and mitigation strategies to ensure equitable performance across diverse patient populations, and secure HIPAA-compliant data handling practices. Through practical labs and real-world case studies, you'll develop skills in model training, hyperparameter optimization, performance evaluation using clinical metrics (sensitivity, specificity, AUC), MLOps implementation with CI/CD pipelines, and creating compelling data visualizations that communicate AI insights to clinical stakeholders.

Détails du module

This foundational module introduces learners to essential machine learning concepts specifically applied to healthcare contexts. Students explore the complete AI model lifecycle from initial data preparation through deployment, gaining hands-on experience with Azure ML Studio's visual interface. The module emphasizes practical application of ML fundamentals while establishing critical validation practices necessary for clinical environments.

Inclus

6 vidéos6 lectures4 devoirs

6 vidéosTotal 19 minutes

Why Machine Learning Revolutionizes Healthcare2 minutes
Building Your First Healthcare ML Model in Azure3 minutes
From Data to Deployment: The Journey3 minutes
End-to-End Model Development in Azure ML4 minutes
When Models Fail: The Importance of Validation2 minutes
Advanced Validation Techniques in Azure ML4 minutes

6 lecturesTotal 315 minutes

Machine Learning Essentials for Healthcare Professionals15 minutes
Hands-on – Readmission Risk Predictor Development90 minutes
The Complete Healthcare AI Model Lifecycle15 minutes
Hands-on – Complete Lifecycle Implementation90 minutes
Clinical Model Validation Strategies15 minutes
Hands-on – Multi-Site Validation Exercise90 minutes

4 devoirsTotal 300 minutes

ML Fundamentals Mastery90 minutes
Lifecycle Management Proficiency90 minutes
Validation Excellence Assessment90 minutes
Machine Learning Foundations and Model Development30 minutes

This module addresses critical challenges in healthcare AI implementation by focusing on bias detection, system reliability, and model interpretability. Learners develop expertise in identifying and mitigating bias in healthcare datasets while implementing fairness constraints and reliability frameworks. The module emphasizes creating interpretable AI solutions that translate complex model outputs into clinically meaningful insights for healthcare professionals.

Inclus

6 vidéos5 lectures5 devoirs

6 vidéosTotal 22 minutes

Hidden Bias, Real Consequences2 minutes
Detecting Bias with Azure Responsible AI Dashboard5 minutes
Building Trust Through Reliable AI2 minutes
Implementing Fairness Constraints in Azure ML5 minutes
Making Black Boxes Transparent2 minutes
Creating Interpretable Clinical AI with Azure5 minutes

5 lecturesTotal 225 minutes

Sources and Impacts of Healthcare AI Bias15 minutes
Hands-on – Bias Detection Workshop90 minutes
Ensuring Healthcare AI Reliability15 minutes
Explainable AI for Clinical Decision-Making15 minutes
Hands-on – Clinical Explanation Design90 minutes

5 devoirsTotal 390 minutes

Bias Identification and Assessment90 minutes
Reliability Engineering for Clinical AI90 minutes
Reliability and Fairness Implementation90 minutes
Interpretation and Translation Mastery90 minutes
AI Bias, Reliability, and Interpretability30 minutes

This module explores specialized applications of AI in medical imaging analysis and patient risk prediction. Students learn to implement computer vision solutions for diagnostic imaging support while developing sophisticated predictive models for clinical risk assessment. The module combines hands-on experience with Azure Cognitive Services and pre-built model libraries to create practical healthcare AI applications.

Inclus

6 vidéos6 lectures4 devoirs

6 vidéosTotal 22 minutes

AI as the Radiologist's Assistant2 minutes
Building a Chest X-Ray Classifier with Azure5 minutes
Predicting the Unpredictable2 minutes
Developing a Readmission Risk Model in Azure ML5 minutes
Standing on the Shoulders of Giants2 minutes
Implementing Pre-Built Models from Azure AI Gallery5 minutes

6 lecturesTotal 315 minutes

Medical Imaging AI Fundamentals15 minutes
Hands-on – Medical Image Analysis Pipeline90 minutes
Clinical Risk Prediction Modeling15 minutes
Hands-on – Comprehensive Risk Prediction System90 minutes
Leveraging Pre-Built Healthcare AI Models15 minutes
Hands-on – Model Library Evaluation and Selection90 minutes

4 devoirsTotal 180 minutes

Medical Imaging AI Proficiency30 minutes
Risk Prediction Excellence90 minutes
Model Library Utilization30 minutes
Medical Imaging and Predictive Analytics30 minutes

This module focuses on transforming healthcare data and AI predictions into actionable visual insights for clinical decision-making. Learners master data integration techniques using Azure Synapse while creating comprehensive dashboards with Power BI. The module emphasizes building visualization solutions that effectively communicate complex healthcare analytics to diverse stakeholder audiences, from clinicians to administrators.

Inclus

6 vidéos6 lectures5 devoirs

6 vidéosTotal 20 minutes

From Data Chaos to Clinical Insights2 minutes
Building a Healthcare Data Pipeline with Azure Synapse4 minutes
Seeing the Story in the Data2 minutes
Creating Clinical Dashboards with Power BI5 minutes
Predictive Analytics Meets Visual Intelligence2 minutes
Integrating ML Models with Power BI Dashboards4 minutes

6 lecturesTotal 315 minutes

Healthcare Data Integration Strategies15 minutes
Hands-on – Multi-Source Data Integration Project90 minutes
Effective Healthcare Data Visualization15 minutes
Hands-on – Comprehensive Healthcare Dashboard Development90 minutes
Integrated Analytics and ML Visualization15 minutes
Hands-on – Predictive Analytics Dashboard Creation90 minutes

5 devoirsTotal 210 minutes

Data Integration Mastery30 minutes
Visualization Excellence30 minutes
Advanced Analytics Integration30 minutes
Healthcare Data Visualization and Analytics30 minutes
Patient Risk Prediction and Visualization System90 minutes

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